1
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Vaughn JN, Korani W, Clevenger J, Ozias-Akins P. Agile Genetics: Single gene resolution without the fuss. Bioessays 2024; 46:e2300206. [PMID: 38769697 DOI: 10.1002/bies.202300206] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2023] [Revised: 03/06/2024] [Accepted: 05/08/2024] [Indexed: 05/22/2024]
Abstract
Gene discovery reveals new biology, expands the utility of marker-assisted selection, and enables targeted mutagenesis. Still, such discoveries can take over a decade. We present a general strategy, "Agile Genetics," that uses nested, structured populations to overcome common limits on gene resolution. Extensive simulation work on realistic genetic architectures shows that, at population sizes of >5000 samples, single gene-resolution can be achieved using bulk segregant pools. At this scale, read depth and technical replication become major drivers of resolution. Emerging enrichment methods to address coverage are on the horizon; we describe one possibility - iterative depth sequencing (ID-seq). In addition, graph-based pangenomics in experimental populations will continue to maximize accuracy and improve interpretation. Based on this merger of agronomic scale with molecular and bioinformatic innovation, we predict a new age of rapid gene discovery.
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Affiliation(s)
| | - Walid Korani
- Hudson-Alpha Institute of Biotechnology, Huntsville, Alabama, USA
| | - Josh Clevenger
- Hudson-Alpha Institute of Biotechnology, Huntsville, Alabama, USA
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2
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Huynh T, Van K, Mian MAR, McHale LK. Single- and multiple-trait quantitative trait locus analyses for seed oil and protein contents of soybean populations with advanced breeding line background. MOLECULAR BREEDING : NEW STRATEGIES IN PLANT IMPROVEMENT 2024; 44:51. [PMID: 39118867 PMCID: PMC11306453 DOI: 10.1007/s11032-024-01489-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/15/2024] [Accepted: 07/24/2024] [Indexed: 08/10/2024]
Abstract
Soybean seed oil and protein contents are negatively correlated, posing challenges to enhance both traits simultaneously. Previous studies have identified numerous oil and protein QTLs via single-trait QTL analysis. Multiple-trait QTL methods were shown to be superior but have not been applied to seed oil and protein contents. Our study aimed to evaluate the effectiveness of single- and multiple-trait multiple interval mapping (ST-MIM and MT-MIM, respectively) for these traits using three recombinant inbred line populations from advanced breeding line crosses tested in four environments. Using original and simulated data, we found that MT-MIM did not outperform ST-MIM for our traits with high heritability (H2 > 0.84). Empirically, MT-MIM confirmed only five out of the seven QTLs detected by ST-MIM, indicating single-trait analysis was sufficient for these traits. All QTLs exerted opposite effects on oil and protein contents with varying protein-to-oil additive effect ratios (-0.4 to -4.8). We calculated the economic impact of the allelic variations via estimated processed values (EPV) using the National Oilseed Processors Association (NOPA) and High Yield + Quality (HY + Q) methods. Oil-increasing alleles had positive effects on both EPVNOPA and EPVHY+Q when the protein-to-oil ratio was low (-0.4 to -0.7). However, when the ratio was high (-4.1 to -4.8), oil-increasing alleles increased EPVNOPA and decreased EPVHY+Q, which penalizes low protein meal. In conclusion, single-trait QTL analysis is adequately effective for high heritability traits like seed oil and protein contents. Additionally, the populations' elite pedigrees and varying protein-to-oil ratios provide potential lines for further yield assessment and direct integration into breeding programs. Supplementary Information The online version contains supplementary material available at 10.1007/s11032-024-01489-2.
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Affiliation(s)
- Tu Huynh
- Department of Horticulture and Crop Science, The Ohio State University, Columbus, OH 43210 USA
| | - Kyujung Van
- Department of Horticulture and Crop Science, The Ohio State University, Columbus, OH 43210 USA
| | - M. A. Rouf Mian
- Department of Crop and Soil Sciences, North Carolina State University, Raleigh, NC 270607 USA
- Soybean and Nitrogen Fixation Unit, USDA-ARS, Raleigh, NC 27607 USA
| | - Leah K. McHale
- Department of Horticulture and Crop Science, The Ohio State University, Columbus, OH 43210 USA
- Soybean Research Center, The Ohio State University, Columbus, OH 43210 USA
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3
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Zhang Z, Gomes Viana JP, Zhang B, Walden KKO, Müller Paul H, Moose SP, Morris GP, Daum C, Barry KW, Shakoor N, Hudson ME. Major impacts of widespread structural variation on sorghum. Genome Res 2024; 34:286-299. [PMID: 38479835 PMCID: PMC10984582 DOI: 10.1101/gr.278396.123] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2023] [Accepted: 01/22/2024] [Indexed: 03/22/2024]
Abstract
Genetic diversity is critical to crop breeding and improvement, and dissection of the genomic variation underlying agronomic traits can both assist breeding and give insight into basic biological mechanisms. Although recent genome analyses in plants reveal many structural variants (SVs), most current studies of crop genetic variation are dominated by single-nucleotide polymorphisms (SNPs). The extent of the impact of SVs on global trait variation, as well as their utility in genome-wide selection, is not yet understood. In this study, we built an SV data set based on whole-genome resequencing of diverse sorghum lines (n = 363), validated the correlation of photoperiod sensitivity and variety type, and identified SV hotspots underlying the divergent evolution of cellulosic and sweet sorghum. In addition, we showed the complementary contribution of SVs for heritability of traits related to sorghum adaptation. Importantly, inclusion of SV polymorphisms in association studies revealed genotype-phenotype associations not observed with SNPs alone. Three-way genome-wide association studies (GWAS) based on whole-genome SNP, SV, and integrated SNP + SV data sets showed substantial associations between SVs and sorghum traits. The addition of SVs to GWAS substantially increased heritability estimates for some traits, indicating their important contribution to functional allelic variation at the genome level. Our discovery of the widespread impacts of SVs on heritable gene expression variation could render a plausible mechanism for their disproportionate impact on phenotypic variation. This study expands our knowledge of SVs and emphasizes the extensive impacts of SVs on sorghum.
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Affiliation(s)
- Zhihai Zhang
- DOE Center for Advanced Bioenergy and Bioproducts Innovation (CABBI), University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, USA
| | - Joao Paulo Gomes Viana
- Department of Crop Sciences, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, USA
| | - Bosen Zhang
- Department of Crop Sciences, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, USA
| | - Kimberly K O Walden
- High Performance Computing in Biology, Carver Biotechnology Center, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, USA
| | - Hans Müller Paul
- DOE Center for Advanced Bioenergy and Bioproducts Innovation (CABBI), University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, USA
| | - Stephen P Moose
- DOE Center for Advanced Bioenergy and Bioproducts Innovation (CABBI), University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, USA
- Department of Crop Sciences, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, USA
| | - Geoffrey P Morris
- Department of Soil and Crop Science, Colorado State University, Fort Collins, Colorado 80523, USA
| | - Chris Daum
- United States Department of Energy Joint Genome Institute, Lawrence Berkeley National Laboratory, Berkeley, California 94720, USA
| | - Kerrie W Barry
- United States Department of Energy Joint Genome Institute, Lawrence Berkeley National Laboratory, Berkeley, California 94720, USA
| | - Nadia Shakoor
- Donald Danforth Plant Science Center, St. Louis, Missouri 63132, USA
| | - Matthew E Hudson
- DOE Center for Advanced Bioenergy and Bioproducts Innovation (CABBI), University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, USA;
- Department of Crop Sciences, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, USA
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4
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Qi Z, Guo C, Li H, Qiu H, Li H, Jong C, Yu G, Zhang Y, Hu L, Wu X, Xin D, Yang M, Liu C, Lv J, Wang X, Kong F, Chen Q. Natural variation in Fatty Acid 9 is a determinant of fatty acid and protein content. PLANT BIOTECHNOLOGY JOURNAL 2024; 22:759-773. [PMID: 37937736 PMCID: PMC10893952 DOI: 10.1111/pbi.14222] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/19/2023] [Revised: 10/12/2023] [Accepted: 10/20/2023] [Indexed: 11/09/2023]
Abstract
Soybean is one of the most economically important crops worldwide and an important source of unsaturated fatty acids and protein for the human diet. Consumer demand for healthy fats and oils is increasing, and the global demand for vegetable oil is expected to double by 2050. Identification of key genes that regulate seed fatty acid content can facilitate molecular breeding of high-quality soybean varieties with enhanced fatty acid profiles. Here, we analysed the genetic architecture underlying variations in soybean seed fatty acid content using 547 accessions, including mainly landraces and cultivars from northeastern China. Through fatty acid profiling, genome re-sequencing, population genomics analyses, and GWAS, we identified a SEIPIN homologue at the FA9 locus as an important contributor to seed fatty acid content. Transgenic and multiomics analyses confirmed that FA9 was a key regulator of seed fatty acid content with pleiotropic effects on seed protein and seed size. We identified two major FA9 haplotypes in 1295 resequenced soybean accessions and assessed their phenotypic effects in a field planting of 424 accessions. Soybean accessions carrying FA9H2 had significantly higher total fatty acid contents and lower protein contents than those carrying FA9H1 . FA9H2 was absent in wild soybeans but present in 13% of landraces and 26% of cultivars, suggesting that it may have been selected during soybean post-domestication improvement. FA9 therefore represents a useful genetic resource for molecular breeding of high-quality soybean varieties with specific seed storage profiles.
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Affiliation(s)
- Zhaoming Qi
- College of AgricultureNortheast Agricultural UniversityHarbinHeilongjiangChina
| | - Chaocheng Guo
- Shanghai Collaborative Innovation Center of Agri‐Seeds, Joint Center for Single Cell Biology, School of Agriculture and BiologyShanghai Jiao Tong UniversityShanghaiChina
| | - Haiyang Li
- Guangdong Provincial Key Laboratory of Plant Adaptation and Molecular Design, Guangzhou Key Laboratory of Crop Gene Editing, Innovative Center of Molecular Genetics and Evolution, School of Life SciencesGuangzhou UniversityGuangzhouChina
| | - Hongmei Qiu
- Soybean Research InstituteJilin Academy of Agricultural Sciences/National Soybean Engineering CenterChangchunChina
| | - Hui Li
- College of AgricultureNortheast Agricultural UniversityHarbinHeilongjiangChina
| | - CholNam Jong
- College of AgricultureNortheast Agricultural UniversityHarbinHeilongjiangChina
| | - Guolong Yu
- Shanghai Collaborative Innovation Center of Agri‐Seeds, Joint Center for Single Cell Biology, School of Agriculture and BiologyShanghai Jiao Tong UniversityShanghaiChina
| | - Yu Zhang
- College of AgricultureNortheast Agricultural UniversityHarbinHeilongjiangChina
| | - Limin Hu
- College of AgricultureNortheast Agricultural UniversityHarbinHeilongjiangChina
| | - Xiaoxia Wu
- College of AgricultureNortheast Agricultural UniversityHarbinHeilongjiangChina
| | - Dawei Xin
- College of AgricultureNortheast Agricultural UniversityHarbinHeilongjiangChina
| | - Mingliang Yang
- College of AgricultureNortheast Agricultural UniversityHarbinHeilongjiangChina
| | - Chunyan Liu
- College of AgricultureNortheast Agricultural UniversityHarbinHeilongjiangChina
| | - Jian Lv
- Department of InnovationSyngenta Biotechnology ChinaBeijingChina
| | - Xu Wang
- Shanghai Collaborative Innovation Center of Agri‐Seeds, Joint Center for Single Cell Biology, School of Agriculture and BiologyShanghai Jiao Tong UniversityShanghaiChina
| | - Fanjiang Kong
- Guangdong Provincial Key Laboratory of Plant Adaptation and Molecular Design, Guangzhou Key Laboratory of Crop Gene Editing, Innovative Center of Molecular Genetics and Evolution, School of Life SciencesGuangzhou UniversityGuangzhouChina
| | - Qingshan Chen
- College of AgricultureNortheast Agricultural UniversityHarbinHeilongjiangChina
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5
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Silva JNB, Bueno RD, de Sousa TDJF, Xavier YPM, Silva LCC, Piovesan ND, Ribeiro C, Dal-Bianco M. Exploring SoySNP50K and USDA Germplasm Collection Data to Find New QTLs Associated with Protein and Oil Content in Brazilian Genotypes. Biochem Genet 2024:10.1007/s10528-024-10698-5. [PMID: 38358588 DOI: 10.1007/s10528-024-10698-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2023] [Accepted: 01/10/2024] [Indexed: 02/16/2024]
Abstract
Genetic diversity within a germplasm collection plays a vital role in the success of breeding programs. However, comprehending this diversity and identifying accessions with desirable traits pose significant challenges. This study utilized publicly available data to investigate SNP markers associated with protein and oil content in Brazilian soybeans. Through this research, twenty-two new QTLs (Quantitative Trait Loci) were identified, and we highlighted the substantial influence of Roanoke, Lee and Bragg ancestor on the genetic makeup of Brazilian soybean varieties. Our findings demonstrate that certain markers are being lost in modern cultivars, while others maintain or even increase their frequency. These observations indicate genomic regions that have undergone selection during soybean introduction in Brazil and could be valuable in breeding programs aimed at enhancing protein or oil content.
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Affiliation(s)
- Jessica Nayara Basílio Silva
- Laboratório de Bioquímica Genética de Plantas, BIOAGRO, Universidade Federal de Viçosa, Viçosa, MG, 21236570-900, Brazil
| | - Rafael Delmond Bueno
- Laboratório de Bioquímica Genética de Plantas, BIOAGRO, Universidade Federal de Viçosa, Viçosa, MG, 21236570-900, Brazil
| | | | - Yan Pablo Moreira Xavier
- Laboratório de Bioquímica Genética de Plantas, BIOAGRO, Universidade Federal de Viçosa, Viçosa, MG, 21236570-900, Brazil
| | - Luiz Claudio Costa Silva
- Departamento de Ciências Biológicas, Universidade Estadual de Feira de Santana, Feira de Santana, BA, 44036-900, Brazil
| | - Newton Deniz Piovesan
- Laboratório de Bioquímica Genética de Plantas, BIOAGRO, Universidade Federal de Viçosa, Viçosa, MG, 21236570-900, Brazil
| | - Cleberson Ribeiro
- Departamento de Biologia Geral, Universidade Federal de Viçosa, Viçosa, MG, 36570-900, Brazil
| | - Maximiller Dal-Bianco
- Laboratório de Bioquímica Genética de Plantas, BIOAGRO, Universidade Federal de Viçosa, Viçosa, MG, 21236570-900, Brazil.
- Departamento de Bioquímica E Biologia Molecular, Universidade Federal de Viçosa, Viçosa, MG, 36570-900, Brazil.
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6
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Souza R, Rouf Mian MA, Vaughn JN, Li Z. Introgression of a Danbaekkong high-protein allele across different genetic backgrounds in soybean. FRONTIERS IN PLANT SCIENCE 2023; 14:1308731. [PMID: 38173927 PMCID: PMC10761420 DOI: 10.3389/fpls.2023.1308731] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/07/2023] [Accepted: 11/28/2023] [Indexed: 01/05/2024]
Abstract
Soybean meal is a major component of livestock feed due to its high content and quality of protein. Understanding the genetic control of protein is essential to develop new cultivars with improved meal protein. Previously, a genomic region on chromosome 20 significantly associated with elevated protein content was identified in the cultivar Danbaekkong. The present research aimed to introgress the Danbaekkong high-protein allele into elite lines with different genetic backgrounds by developing and deploying robust DNA markers. A multiparent population consisting of 10 F5-derived populations with a total of 1,115 recombinant inbred lines (RILs) was developed using "Benning HP" as the donor parent of the Danbaekkong high-protein allele. A new functional marker targeting the 321-bp insertion in the gene Glyma.20g085100 was developed and used to track the Danbaekkong high-protein allele across the different populations and enable assessment of its effect and stability. Across all populations, the high-protein allele consistently increased the content, with an increase of 3.3% in seed protein. A total of 103 RILs were selected from the multiparent population for yield testing in five environments to assess the impact of the high-protein allele on yield and to enable the selection of new breeding lines with high protein and high yield. The results indicated that the high-protein allele impacts yield negatively in general; however, it is possible to select high-yielding lines with high protein content. An analysis of inheritance of the Chr 20 high-protein allele in Danbaekkong indicated that it originated from a Glycine soja line (PI 163453) and is the same as other G. soja lines studied. A survey of the distribution of the allele across 79 G. soja accessions and 35 Glycine max ancestors of North American soybean cultivars showed that the high-protein allele is present in all G. soja lines evaluated but not in any of the 35 North American soybean ancestors. These results demonstrate that G. soja accessions are a valuable source of favorable alleles for improvement of protein composition.
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Affiliation(s)
- Renan Souza
- Department of Crop and Soil Sciences, University of Georgia, Athens, GA, United States
| | - M. A. Rouf Mian
- Soybean and Nitrogen Fixation Research Unit, United States Department of Agriculture - Agricultural Research Service (USDA-ARS), Raleigh, NC, United States
| | - Justin N. Vaughn
- Department of Crop and Soil Sciences, University of Georgia, Athens, GA, United States
- Genomics and Bioinformatics Research Unit, United States Department of Agriculture - Agricultural Research Service (USDA-ARS), Athens, GA, United States
| | - Zenglu Li
- Department of Crop and Soil Sciences, University of Georgia, Athens, GA, United States
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7
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Singer WM, Lee YC, Shea Z, Vieira CC, Lee D, Li X, Cunicelli M, Kadam SS, Khan MAW, Shannon G, Mian MAR, Nguyen HT, Zhang B. Soybean genetics, genomics, and breeding for improving nutritional value and reducing antinutritional traits in food and feed. THE PLANT GENOME 2023; 16:e20415. [PMID: 38084377 DOI: 10.1002/tpg2.20415] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/21/2023] [Revised: 10/25/2023] [Accepted: 10/27/2023] [Indexed: 12/22/2023]
Abstract
Soybean [Glycine max (L.) Merr.] is a globally important crop due to its valuable seed composition, versatile feed, food, and industrial end-uses, and consistent genetic gain. Successful genetic gain in soybean has led to widespread adaptation and increased value for producers, processors, and consumers. Specific focus on the nutritional quality of soybean seed composition for food and feed has further elucidated genetic knowledge and bolstered breeding progress. Seed components are historical and current targets for soybean breeders seeking to improve nutritional quality of soybean. This article reviews genetic and genomic foundations for improvement of nutritionally important traits, such as protein and amino acids, oil and fatty acids, carbohydrates, and specific food-grade considerations; discusses the application of advanced breeding technology such as CRISPR/Cas9 in creating seed composition variations; and provides future directions and breeding recommendations regarding soybean seed composition traits.
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Affiliation(s)
- William M Singer
- School of Plant and Environmental Sciences, Virginia Polytechnic Institute and State University, Blacksburg, Virginia, USA
| | - Yi-Chen Lee
- Department of Agriculture, Fort Hays State University, Hays, Kansas, USA
| | - Zachary Shea
- School of Plant and Environmental Sciences, Virginia Polytechnic Institute and State University, Blacksburg, Virginia, USA
| | - Caio Canella Vieira
- Department of Crop, Soil, and Environmental Sciences, University of Arkansas, Fayetteville, Arkansas, USA
| | - Dongho Lee
- Fisher Delta Research, Extension, and Education Center, University of Missouri, Portageville, Missouri, USA
| | - Xiaoying Li
- School of Plant and Environmental Sciences, Virginia Polytechnic Institute and State University, Blacksburg, Virginia, USA
| | - Mia Cunicelli
- Soybean and Nitrogen Fixation Research Unit, USDA-ARS, Raleigh, North Carolina, USA
| | - Shaila S Kadam
- Division of Plant Science and Technology, University of Missouri, Columbia, Missouri, USA
| | | | - Grover Shannon
- Fisher Delta Research, Extension, and Education Center, University of Missouri, Portageville, Missouri, USA
| | - M A Rouf Mian
- Soybean and Nitrogen Fixation Research Unit, USDA-ARS, Raleigh, North Carolina, USA
| | - Henry T Nguyen
- Division of Plant Science and Technology, University of Missouri, Columbia, Missouri, USA
| | - Bo Zhang
- School of Plant and Environmental Sciences, Virginia Polytechnic Institute and State University, Blacksburg, Virginia, USA
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8
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Vuong TD, Florez-Palacios L, Mozzoni L, Clubb M, Quigley C, Song Q, Kadam S, Yuan Y, Chan TF, Mian MAR, Nguyen HT. Genomic analysis and characterization of new loci associated with seed protein and oil content in soybeans. THE PLANT GENOME 2023; 16:e20400. [PMID: 37940622 DOI: 10.1002/tpg2.20400] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/13/2023] [Revised: 09/30/2023] [Accepted: 10/02/2023] [Indexed: 11/10/2023]
Abstract
Breeding for increased protein without a reduction in oil content in soybeans [Glycine max (L.) Merr.] is a challenge for soybean breeders but an expected goal. Many efforts have been made to develop new soybean varieties with high yield in combination with desirable protein and/or oil traits. An elite line, R05-1415, was reported to be high yielding, high protein, and low oil. Several significant quantitative trait loci (QTL) for protein and oil were reported in this line, but many of them were unstable across environments or genetic backgrounds. Thus, a new study under multiple field environments using the Infinium BARCSoySNP6K BeadChips was conducted to detect and confirm stable genomic loci for these traits. Genetic analyses consistently detected a single major genomic locus conveying these two traits with remarkably high phenotypic variation explained (R2 ), varying between 24.2% and 43.5%. This new genomic locus is located between 25.0 and 26.7 Mb, distant from the previously reported QTL and did not overlap with other commonly reported QTL and the recently cloned gene Glyma.20G085100. Homolog analysis indicated that this QTL did not result from the paracentric chromosome inversion with an adjacent genomic fragment that harbors the reported QTL. The pleiotropic effect of this QTL could be a challenge for improving protein and oil simultaneously; however, a further study of four candidate genes with significant expressions in the seed developmental stages coupled with haplotype analysis may be able to pinpoint causative genes. The functionality and roles of these genes can be determined and characterized, which lay a solid foundation for the improvement of protein and oil content in soybeans.
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Affiliation(s)
- Tri D Vuong
- Division of Plant Science and Technology, University of Missouri, Columbia, Missouri, USA
| | | | - Leandro Mozzoni
- Crop, Soil, and Environmental Sciences, University of Arkansas, Fayetteville, Arkansas, USA
| | - Michael Clubb
- Division of Plant Science and Technology, the Fisher Delta Research, Extension and Education Center (FDREEC), University of Missouri, Portageville, Missouri, USA
| | - Chuck Quigley
- Soybean Genomics and Improvement Laboratory, USDA-ARS, Beltsville, Maryland, USA
| | - Qijian Song
- Soybean Genomics and Improvement Laboratory, USDA-ARS, Beltsville, Maryland, USA
| | - Shaila Kadam
- Division of Plant Science and Technology, University of Missouri, Columbia, Missouri, USA
| | - Yuxuan Yuan
- School of Life Sciences and State Key Laboratory of Agrobiotechnology, The Chinese University of Hong Kong, Hong Kong, SAR, China
| | - Ting Fung Chan
- School of Life Sciences and State Key Laboratory of Agrobiotechnology, The Chinese University of Hong Kong, Hong Kong, SAR, China
| | | | - Henry T Nguyen
- Division of Plant Science and Technology, University of Missouri, Columbia, Missouri, USA
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9
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Lemay MA, de Ronne M, Bélanger R, Belzile F. k-mer-based GWAS enhances the discovery of causal variants and candidate genes in soybean. THE PLANT GENOME 2023; 16:e20374. [PMID: 37596724 DOI: 10.1002/tpg2.20374] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/04/2023] [Accepted: 07/19/2023] [Indexed: 08/20/2023]
Abstract
Genome-wide association studies (GWAS) are powerful statistical methods that detect associations between genotype and phenotype at genome scale. Despite their power, GWAS frequently fail to pinpoint the causal variant or the gene controlling a given trait in crop species. Assessing genetic variants other than single-nucleotide polymorphisms (SNPs) could alleviate this problem. In this study, we tested the potential of structural variant (SV)- and k-mer-based GWAS in soybean by applying these methods as well as conventional SNP/indel-based GWAS to 13 traits. We assessed the performance of each GWAS approach based on loci for which the causal genes or variants were known from previous genetic studies. We found that k-mer-based GWAS was the most versatile approach and the best at pinpointing causal variants or candidate genes. Moreover, k-mer-based analyses identified promising candidate genes for loci related to pod color, pubescence form, and resistance to Phytophthora sojae. In our dataset, SV-based GWAS did not add value compared to k-mer-based GWAS and may not be worth the time and computational resources invested. Despite promising results, significant challenges remain regarding the downstream analysis of k-mer-based GWAS. Notably, better methods are needed to associate significant k-mers with sequence variation. Our results suggest that coupling k-mer- and SNP/indel-based GWAS is a powerful approach for discovering candidate genes in crop species.
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Affiliation(s)
- Marc-André Lemay
- Département de phytologie, Université Laval, Québec, QC, Canada
- Institut de biologie intégrative et des systèmes, Université Laval, Québec, QC, Canada
- Centre de recherche et d'innovation sur les végétaux, Université Laval, Québec, QC, Canada
| | - Maxime de Ronne
- Département de phytologie, Université Laval, Québec, QC, Canada
- Institut de biologie intégrative et des systèmes, Université Laval, Québec, QC, Canada
- Centre de recherche et d'innovation sur les végétaux, Université Laval, Québec, QC, Canada
| | - Richard Bélanger
- Département de phytologie, Université Laval, Québec, QC, Canada
- Institut de biologie intégrative et des systèmes, Université Laval, Québec, QC, Canada
- Centre de recherche et d'innovation sur les végétaux, Université Laval, Québec, QC, Canada
| | - François Belzile
- Département de phytologie, Université Laval, Québec, QC, Canada
- Institut de biologie intégrative et des systèmes, Université Laval, Québec, QC, Canada
- Centre de recherche et d'innovation sur les végétaux, Université Laval, Québec, QC, Canada
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10
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Park HR, Seo JH, Kang BK, Kim JH, Heo SV, Choi MS, Ko JY, Kim CS. QTLs and Candidate Genes for Seed Protein Content in Two Recombinant Inbred Line Populations of Soybean. PLANTS (BASEL, SWITZERLAND) 2023; 12:3589. [PMID: 37896053 PMCID: PMC10610525 DOI: 10.3390/plants12203589] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/11/2023] [Revised: 10/11/2023] [Accepted: 10/12/2023] [Indexed: 10/29/2023]
Abstract
This study aimed to discover the quantitative trait loci (QTL) associated with a high seed protein content in soybean and unravel the potential candidate genes. We developed two recombinant inbred line populations: YS and SI, by crossing Saedanbaek (high protein) with YS2035-B-91-1-B-1 (low protein) and Saedanbaek with Ilmi (low protein), respectively, and evaluated the protein content for three consecutive years. Using single-nucleotide polymorphism (SNP)-marker-based linkage maps, four QTLs were located on chromosomes 15, 18, and 20 with high logarithm of odds values (5.9-55.0), contributing 5.5-66.0% phenotypic variance. In all three experimental years, qPSD20-1 and qPSD20-2 were stable and identified in overlapping positions in the YS and SI populations, respectively. Additionally, novel QTLs were identified on chromosomes 15 and 18. Considering the allelic sequence variation between parental lines, 28 annotated genes related to soybean seed protein-including starch, lipid, and fatty acid biosynthesis-related genes-were identified within the QTL regions. These genes could potentially affect protein accumulation during seed development, as well as sucrose and oil metabolism. Overall, this study offers insights into the genetic mechanisms underlying a high soybean protein content. The identified potential candidate genes can aid marker-assisted selection for developing soybean lines with an increased protein content.
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Affiliation(s)
| | - Jeong Hyun Seo
- Department of Southern Area Crop Science, National Institute of Crop Science, Rural Development Administration, Miryang 50424, Republic of Korea; (H.R.P.); (B.K.K.); (J.H.K.); (S.V.H.); (M.S.C.); (J.Y.K.); (C.S.K.)
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11
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Hooker JC, Smith M, Zapata G, Charette M, Luckert D, Mohr RM, Daba KA, Warkentin TD, Hadinezhad M, Barlow B, Hou A, Lefebvre F, Golshani A, Cober ER, Samanfar B. Differential gene expression provides leads to environmentally regulated soybean seed protein content. FRONTIERS IN PLANT SCIENCE 2023; 14:1260393. [PMID: 37790790 PMCID: PMC10544915 DOI: 10.3389/fpls.2023.1260393] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/17/2023] [Accepted: 08/23/2023] [Indexed: 10/05/2023]
Abstract
Soybean is an important global source of plant-based protein. A persistent trend has been observed over the past two decades that soybeans grown in western Canada have lower seed protein content than soybeans grown in eastern Canada. In this study, 10 soybean genotypes ranging in average seed protein content were grown in an eastern location (control) and three western locations (experimental) in Canada. Seed protein and oil contents were measured for all lines in each location. RNA-sequencing and differential gene expression analysis were used to identify differentially expressed genes that may account for relatively low protein content in western-grown soybeans. Differentially expressed genes were enriched for ontologies and pathways that included amino acid biosynthesis, circadian rhythm, starch metabolism, and lipid biosynthesis. Gene ontology, pathway mapping, and quantitative trait locus (QTL) mapping collectively provide a close inspection of mechanisms influencing nitrogen assimilation and amino acid biosynthesis between soybeans grown in the East and West. It was found that western-grown soybeans had persistent upregulation of asparaginase (an asparagine hydrolase) and persistent downregulation of asparagine synthetase across 30 individual differential expression datasets. This specific difference in asparagine metabolism between growing environments is almost certainly related to the observed differences in seed protein content because of the positive correlation between seed protein content at maturity and free asparagine in the developing seed. These results provided pointed information on seed protein-related genes influenced by environment. This information is valuable for breeding programs and genetic engineering of geographically optimized soybeans.
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Affiliation(s)
- Julia C. Hooker
- Ottawa Research and Development Centre, Agriculture and Agri-Food Canada, Ottawa, ON, Canada
- Department of Biology, Ottawa Institute of Systems Biology, Carleton University, Ottawa, ON, Canada
| | - Myron Smith
- Department of Biology, Ottawa Institute of Systems Biology, Carleton University, Ottawa, ON, Canada
| | - Gerardo Zapata
- Canadian Centre for Computational Genomics, Montréal, QC, Canada
| | - Martin Charette
- Ottawa Research and Development Centre, Agriculture and Agri-Food Canada, Ottawa, ON, Canada
| | - Doris Luckert
- Ottawa Research and Development Centre, Agriculture and Agri-Food Canada, Ottawa, ON, Canada
| | - Ramona M. Mohr
- Brandon Research Centre, Agriculture and Agri-Food Canada, Brandon, MB, Canada
| | - Ketema A. Daba
- Crop Development Centre, University of Saskatchewan, Saskatoon, SK, Canada
| | | | - Mehri Hadinezhad
- Ottawa Research and Development Centre, Agriculture and Agri-Food Canada, Ottawa, ON, Canada
| | - Brent Barlow
- Crop Development Centre, University of Saskatchewan, Saskatoon, SK, Canada
| | - Anfu Hou
- Morden Research and Development Centre, Agriculture and Agri-Food Canada, Morden, MB, Canada
| | | | - Ashkan Golshani
- Department of Biology, Ottawa Institute of Systems Biology, Carleton University, Ottawa, ON, Canada
| | - Elroy R. Cober
- Ottawa Research and Development Centre, Agriculture and Agri-Food Canada, Ottawa, ON, Canada
| | - Bahram Samanfar
- Ottawa Research and Development Centre, Agriculture and Agri-Food Canada, Ottawa, ON, Canada
- Department of Biology, Ottawa Institute of Systems Biology, Carleton University, Ottawa, ON, Canada
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12
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Clevinger EM, Biyashev R, Haak D, Song Q, Pilot G, Saghai Maroof MA. Identification of quantitative trait loci controlling soybean seed protein and oil content. PLoS One 2023; 18:e0286329. [PMID: 37352204 PMCID: PMC10289428 DOI: 10.1371/journal.pone.0286329] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2022] [Accepted: 05/15/2023] [Indexed: 06/25/2023] Open
Abstract
Soybean is a major source of seed protein and oil globally with an average composition of 40% protein and 20% oil in the seed. The goal of this study was to identify quantitative trait loci (QTL) conferring seed protein and oil content utilizing a population constructed by crossing an above average protein content line, PI 399084 to another line that had a low protein content value, PI 507429, both from the USDA soybean germplasm collection. The recombinant inbred line (RIL) population, PI 507429 x PI 399084, was evaluated in two replications over four years (2018-2021); the seeds were analyzed for seed protein and oil content using near-infrared reflectance spectroscopy. The recombinant inbred lines and the two parents were re-sequenced using genotyping by sequencing. A total of 12,761 molecular markers, which came from genotyping by sequencing, the SoySNP6k BeadChip and selected simple sequence repeat (SSR) markers from known protein QTL chromosomal regions were used for mapping. One QTL was identified on chromosome 2 explaining up to 56.8% of the variation for seed protein content and up to 43% for seed oil content. Another QTL identified on chromosome 15 explained up to 27.2% of the variation for seed protein and up to 41% of the variation for seed oil content. The protein and oil QTLs of this study and their associated molecular markers will be useful in breeding to improve nutritional quality in soybean.
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Affiliation(s)
- Elizabeth M. Clevinger
- School of Plant and Environmental Sciences, Virginia Tech, Blacksburg, Virginia, United States of America
| | - Ruslan Biyashev
- School of Plant and Environmental Sciences, Virginia Tech, Blacksburg, Virginia, United States of America
| | - David Haak
- School of Plant and Environmental Sciences, Virginia Tech, Blacksburg, Virginia, United States of America
| | - Qijian Song
- Soybean Genomics and Improvement Lab, United States Department of Agriculture-Agricultural Research Service, Beltsville, Maryland, United States of America
| | - Guillaume Pilot
- School of Plant and Environmental Sciences, Virginia Tech, Blacksburg, Virginia, United States of America
| | - M. A. Saghai Maroof
- School of Plant and Environmental Sciences, Virginia Tech, Blacksburg, Virginia, United States of America
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13
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Kim WJ, Kang BH, Kang S, Shin S, Chowdhury S, Jeong SC, Choi MS, Park SK, Moon JK, Ryu J, Ha BK. A Genome-Wide Association Study of Protein, Oil, and Amino Acid Content in Wild Soybean ( Glycine soja). PLANTS (BASEL, SWITZERLAND) 2023; 12:1665. [PMID: 37111888 PMCID: PMC10143452 DOI: 10.3390/plants12081665] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/23/2023] [Revised: 04/07/2023] [Accepted: 04/13/2023] [Indexed: 06/19/2023]
Abstract
Soybean (Glycine max L.) is a globally important source of plant proteins, oils, and amino acids for both humans and livestock. Wild soybean (Glycine soja Sieb. and Zucc.), the ancestor of cultivated soybean, could be a useful genetic source for increasing these components in soybean crops. In this study, 96,432 single-nucleotide polymorphisms (SNPs) across 203 wild soybean accessions from the 180K Axiom® Soya SNP array were investigated using an association analysis. Protein and oil content exhibited a highly significant negative correlation, while the 17 amino acids exhibited a highly significant positive correlation with each other. A genome-wide association study (GWAS) was conducted on the protein, oil, and amino acid content using the 203 wild soybean accessions. A total of 44 significant SNPs were associated with protein, oil, and amino acid content. Glyma.11g015500 and Glyma.20g050300, which contained SNPs detected from the GWAS, were selected as novel candidate genes for the protein and oil content, respectively. In addition, Glyma.01g053200 and Glyma.03g239700 were selected as novel candidate genes for nine of the amino acids (Ala, Asp, Glu, Gly, Leu, Lys, Pro, Ser, and Thr). The identification of the SNP markers related to protein, oil, and amino acid content reported in the present study is expected to help improve the quality of selective breeding programs for soybeans.
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Affiliation(s)
- Woon Ji Kim
- Advanced Radiation Technology Institute, Korea Atomic Energy Research Institute, Jeongup 56212, Republic of Korea; (W.J.K.); (J.R.)
| | - Byeong Hee Kang
- Department of Applied Plant Science, Chonnam National University, Gwangju 61186, Republic of Korea; (B.H.K.); (S.K.); (S.S.); (S.C.)
- BK21 FOUR Center for IT-Bio Convergence System Agriculture, Chonnam National University, Gwangju 61186, Republic of Korea
| | - Sehee Kang
- Department of Applied Plant Science, Chonnam National University, Gwangju 61186, Republic of Korea; (B.H.K.); (S.K.); (S.S.); (S.C.)
- BK21 FOUR Center for IT-Bio Convergence System Agriculture, Chonnam National University, Gwangju 61186, Republic of Korea
| | - Seoyoung Shin
- Department of Applied Plant Science, Chonnam National University, Gwangju 61186, Republic of Korea; (B.H.K.); (S.K.); (S.S.); (S.C.)
| | - Sreeparna Chowdhury
- Department of Applied Plant Science, Chonnam National University, Gwangju 61186, Republic of Korea; (B.H.K.); (S.K.); (S.S.); (S.C.)
| | - Soon-Chun Jeong
- Bio-Evaluation Center, Korea Research Institute of Bioscience and Biotechnology, Cheongju 28116, Republic of Korea;
| | - Man-Soo Choi
- National Institute of Crop Science, RDA, Wanju 55365, Republic of Korea; (M.-S.C.); (S.-K.P.); (J.-K.M.)
| | - Soo-Kwon Park
- National Institute of Crop Science, RDA, Wanju 55365, Republic of Korea; (M.-S.C.); (S.-K.P.); (J.-K.M.)
| | - Jung-Kyung Moon
- National Institute of Crop Science, RDA, Wanju 55365, Republic of Korea; (M.-S.C.); (S.-K.P.); (J.-K.M.)
| | - Jaihyunk Ryu
- Advanced Radiation Technology Institute, Korea Atomic Energy Research Institute, Jeongup 56212, Republic of Korea; (W.J.K.); (J.R.)
| | - Bo-Keun Ha
- Department of Applied Plant Science, Chonnam National University, Gwangju 61186, Republic of Korea; (B.H.K.); (S.K.); (S.S.); (S.C.)
- BK21 FOUR Center for IT-Bio Convergence System Agriculture, Chonnam National University, Gwangju 61186, Republic of Korea
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14
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Liu S, Liu Z, Hou X, Li X. Genetic mapping and functional genomics of soybean seed protein. MOLECULAR BREEDING : NEW STRATEGIES IN PLANT IMPROVEMENT 2023; 43:29. [PMID: 37313523 PMCID: PMC10248706 DOI: 10.1007/s11032-023-01373-5] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/29/2022] [Accepted: 03/25/2023] [Indexed: 06/15/2023]
Abstract
Soybean is an utterly important crop for high-quality meal protein and vegetative oil. Soybean seed protein content has become a key factor in nutrients for livestock feed as well as human dietary consumption. Genetic improvement of soybean seed protein is highly desired to meet the demands of rapidly growing world population. Molecular mapping and genomic analysis in soybean have identified many quantitative trait loci (QTL) underlying seed protein content control. Exploring the mechanisms of seed storage protein regulation will be helpful to achieve the improvement of protein content. However, the practice of breeding higher protein soybean is challenging because soybean seed protein is negatively correlated with seed oil content and yield. To overcome the limitation of such inverse relationship, deeper insights into the property and genetic control of seed protein are required. Recent advances of soybean genomics have strongly enhanced the understandings for molecular mechanisms of soybean with better seed quality. Here, we review the research progress in the genetic characteristics of soybean storage protein, and up-to-date advances of molecular mappings and genomics of soybean protein. The key factors underlying the mechanisms of the negative correlation between protein and oil in soybean seeds are elaborated. We also briefly discuss the future prospects of breaking the bottleneck of the negative correlation to develop high protein soybean without penalty of oil and yield. Supplementary Information The online version contains supplementary material available at 10.1007/s11032-023-01373-5.
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Affiliation(s)
- Shu Liu
- Guangdong Provincial Key Laboratory of Applied Botany & Key Laboratory of South China Agricultural Plant Molecular Analysis and Genetic Improvement, South China Botanical Garden, Chinese Academy of Sciences, Guangzhou, 510650 China
- University of Chinese Academy of Sciences, Beijing, 100049 China
| | - Zhaojun Liu
- Heilongjiang Academy of Agricultural Sciences, Harbin, 150086 China
| | - Xingliang Hou
- Guangdong Provincial Key Laboratory of Applied Botany & Key Laboratory of South China Agricultural Plant Molecular Analysis and Genetic Improvement, South China Botanical Garden, Chinese Academy of Sciences, Guangzhou, 510650 China
- Hainan Yazhou Bay Seed Laboratory, Sanya, 572025 China
| | - Xiaoming Li
- Guangdong Provincial Key Laboratory of Applied Botany & Key Laboratory of South China Agricultural Plant Molecular Analysis and Genetic Improvement, South China Botanical Garden, Chinese Academy of Sciences, Guangzhou, 510650 China
- Hainan Yazhou Bay Seed Laboratory, Sanya, 572025 China
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15
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Duan Z, Li Q, Wang H, He X, Zhang M. Genetic regulatory networks of soybean seed size, oil and protein contents. FRONTIERS IN PLANT SCIENCE 2023; 14:1160418. [PMID: 36959925 PMCID: PMC10028097 DOI: 10.3389/fpls.2023.1160418] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/07/2023] [Accepted: 02/24/2023] [Indexed: 06/18/2023]
Abstract
As a leading oilseed crop that supplies plant oil and protein for daily human life, increasing yield and improving nutritional quality (high oil or protein) are the top two fundamental goals of soybean breeding. Seed size is one of the most critical factors determining soybean yield. Seed size, oil and protein contents are complex quantitative traits governed by genetic and environmental factors during seed development. The composition and quantity of seed storage reserves directly affect seed size. In general, oil and protein make up almost 60% of the total storage of soybean seed. Therefore, soybean's seed size, oil, or protein content are highly correlated agronomical traits. Increasing seed size helps increase soybean yield and probably improves seed quality. Similarly, rising oil and protein contents improves the soybean's nutritional quality and will likely increase soybean yield. Due to the importance of these three seed traits in soybean breeding, extensive studies have been conducted on their underlying quantitative trait locus (QTLs) or genes and the dissection of their molecular regulatory pathways. This review summarized the progress in functional genome controlling soybean seed size, oil and protein contents in recent decades, and presented the challenges and prospects for developing high-yield soybean cultivars with high oil or protein content. In the end, we hope this review will be helpful to the improvement of soybean yield and quality in the future breeding process.
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Affiliation(s)
- Zongbiao Duan
- Hainan Yazhou Bay Seed Laboratory, Sanya, China
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing, China
| | - Qing Li
- State Key Laboratory of Rice Biology and Breeding, China National Rice Research Institute, Chinese Academy of Agricultural Sciences, Hangzhou, China
| | - Hong Wang
- State Key Laboratory of Rice Biology and Breeding, China National Rice Research Institute, Chinese Academy of Agricultural Sciences, Hangzhou, China
| | - Xuemei He
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing, China
| | - Min Zhang
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing, China
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16
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Kim WJ, Kang BH, Moon CY, Kang S, Shin S, Chowdhury S, Choi MS, Park SK, Moon JK, Ha BK. Quantitative Trait Loci (QTL) Analysis of Seed Protein and Oil Content in Wild Soybean ( Glycine soja). Int J Mol Sci 2023; 24:ijms24044077. [PMID: 36835486 PMCID: PMC9959443 DOI: 10.3390/ijms24044077] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2023] [Revised: 02/10/2023] [Accepted: 02/13/2023] [Indexed: 02/22/2023] Open
Abstract
Soybean seeds consist of approximately 40% protein and 20% oil, making them one of the world's most important cultivated legumes. However, the levels of these compounds are negatively correlated with each other and regulated by quantitative trait loci (QTL) that are controlled by several genes. In this study, a total of 190 F2 and 90 BC1F2 plants derived from a cross of Daepung (Glycine max) with GWS-1887 (G. soja, a source of high protein), were used for the QTL analysis of protein and oil content. In the F2:3 populations, the average protein and oil content was 45.52% and 11.59%, respectively. A QTL associated with protein levels was detected at Gm20_29512680 on chr. 20 with a likelihood of odds (LOD) of 9.57 and an R2 of 17.2%. A QTL associated with oil levels was also detected at Gm15_3621773 on chr. 15 (LOD: 5.80; R2: 12.2%). In the BC1F2:3 populations, the average protein and oil content was 44.25% and 12.14%, respectively. A QTL associated with both protein and oil content was detected at Gm20_27578013 on chr. 20 (LOD: 3.77 and 3.06; R2 15.8% and 10.7%, respectively). The crossover to the protein content of BC1F3:4 population was identified by SNP marker Gm20_32603292. Based on these results, two genes, Glyma.20g088000 (S-adenosyl-l-methionine-dependent methyltransferases) and Glyma.20g088400 (oxidoreductase, 2-oxoglutarate-Fe(II) oxygenase family protein), in which the amino acid sequence had changed and a stop codon was generated due to an InDel in the exon region, were identified.
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Affiliation(s)
- Woon Ji Kim
- Department of Applied Plant Science, Chonnam National University, Gwangju 61186, Republic of Korea
| | - Byeong Hee Kang
- Department of Applied Plant Science, Chonnam National University, Gwangju 61186, Republic of Korea
- BK21 FOUR Center for IT-Bio Convergence System Agriculture, Chonnam National University, Gwangju 61186, Republic of Korea
| | - Chang Yeok Moon
- Department of Applied Plant Science, Chonnam National University, Gwangju 61186, Republic of Korea
- BK21 FOUR Center for IT-Bio Convergence System Agriculture, Chonnam National University, Gwangju 61186, Republic of Korea
| | - Sehee Kang
- Department of Applied Plant Science, Chonnam National University, Gwangju 61186, Republic of Korea
- BK21 FOUR Center for IT-Bio Convergence System Agriculture, Chonnam National University, Gwangju 61186, Republic of Korea
| | - Seoyoung Shin
- Department of Applied Plant Science, Chonnam National University, Gwangju 61186, Republic of Korea
| | - Sreeparna Chowdhury
- Department of Applied Plant Science, Chonnam National University, Gwangju 61186, Republic of Korea
| | - Man-Soo Choi
- National Institute of Crop Science, Rural Development Administration (RDA), Wanju 55365, Republic of Korea
| | - Soo-Kwon Park
- National Institute of Crop Science, Rural Development Administration (RDA), Wanju 55365, Republic of Korea
| | - Jung-Kyung Moon
- National Institute of Crop Science, Rural Development Administration (RDA), Wanju 55365, Republic of Korea
| | - Bo-Keun Ha
- Department of Applied Plant Science, Chonnam National University, Gwangju 61186, Republic of Korea
- BK21 FOUR Center for IT-Bio Convergence System Agriculture, Chonnam National University, Gwangju 61186, Republic of Korea
- Correspondence: ; Tel.: +82-62-530-2055
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17
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Du H, Fang C, Li Y, Kong F, Liu B. Understandings and future challenges in soybean functional genomics and molecular breeding. JOURNAL OF INTEGRATIVE PLANT BIOLOGY 2023; 65:468-495. [PMID: 36511121 DOI: 10.1111/jipb.13433] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/04/2022] [Accepted: 12/11/2022] [Indexed: 06/17/2023]
Abstract
Soybean (Glycine max) is a major source of plant protein and oil. Soybean breeding has benefited from advances in functional genomics. In particular, the release of soybean reference genomes has advanced our understanding of soybean adaptation to soil nutrient deficiencies, the molecular mechanism of symbiotic nitrogen (N) fixation, biotic and abiotic stress tolerance, and the roles of flowering time in regional adaptation, plant architecture, and seed yield and quality. Nevertheless, many challenges remain for soybean functional genomics and molecular breeding, mainly related to improving grain yield through high-density planting, maize-soybean intercropping, taking advantage of wild resources, utilization of heterosis, genomic prediction and selection breeding, and precise breeding through genome editing. This review summarizes the current progress in soybean functional genomics and directs future challenges for molecular breeding of soybean.
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Affiliation(s)
- Haiping Du
- Guangdong Key Laboratory of Plant Adaptation and Molecular Design, Guangzhou Key Laboratory of Crop Gene Editing, Innovative Center of Molecular Genetics and Evolution, School of Life Sciences, Guangzhou University, Guangzhou, 510006, China
| | - Chao Fang
- Guangdong Key Laboratory of Plant Adaptation and Molecular Design, Guangzhou Key Laboratory of Crop Gene Editing, Innovative Center of Molecular Genetics and Evolution, School of Life Sciences, Guangzhou University, Guangzhou, 510006, China
| | - Yaru Li
- Guangdong Key Laboratory of Plant Adaptation and Molecular Design, Guangzhou Key Laboratory of Crop Gene Editing, Innovative Center of Molecular Genetics and Evolution, School of Life Sciences, Guangzhou University, Guangzhou, 510006, China
| | - Fanjiang Kong
- Guangdong Key Laboratory of Plant Adaptation and Molecular Design, Guangzhou Key Laboratory of Crop Gene Editing, Innovative Center of Molecular Genetics and Evolution, School of Life Sciences, Guangzhou University, Guangzhou, 510006, China
| | - Baohui Liu
- Guangdong Key Laboratory of Plant Adaptation and Molecular Design, Guangzhou Key Laboratory of Crop Gene Editing, Innovative Center of Molecular Genetics and Evolution, School of Life Sciences, Guangzhou University, Guangzhou, 510006, China
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18
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Luo S, Jia J, Liu R, Wei R, Guo Z, Cai Z, Chen B, Liang F, Xia Q, Nian H, Cheng Y. Identification of major QTLs for soybean seed size and seed weight traits using a RIL population in different environments. FRONTIERS IN PLANT SCIENCE 2023; 13:1094112. [PMID: 36714756 PMCID: PMC9874164 DOI: 10.3389/fpls.2022.1094112] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/09/2022] [Accepted: 12/15/2022] [Indexed: 06/18/2023]
Abstract
INTRODUCTION The seed weight of soybean [Glycine max (L.) Merr.] is one of the major traits that determine soybean yield and is closely related to seed size. However, the genetic basis of the synergistic regulation of traits related to soybean yield is unclear. METHODS To understand the molecular genetic basis for the formation of soybean yield traits, the present study focused on QTLs mapping for seed size and weight traits in different environments and target genes mining. RESULTS A total of 85 QTLs associated with seed size and weight traits were identified using a recombinant inbred line (RIL) population developed from Guizao1×B13 (GB13). We also detected 18 environmentally stable QTLs. Of these, qSL-3-1 was a novel QTL with a stable main effect associated with seed length. It was detected in all environments, three of which explained more than 10% of phenotypic variance (PV), with a maximum of 15.91%. In addition, qSW-20-3 was a novel QTL with a stable main effect associated with seed width, which was identified in four environments. And the amount of phenotypic variance explained (PVE) varied from 9.22 to 21.93%. Five QTL clusters associated with both seed size and seed weight were summarized by QTL cluster identification. Fifteen candidate genes that may be involved in regulating soybean seed size and weight were also screened based on gene function annotation and GO enrichment analysis. DISCUSSION The results provide a biologically basic reference for understanding the formation of soybean seed size and weight traits.
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Affiliation(s)
- Shilin Luo
- The State Key Laboratory for Conservation and Utilization of Subtropical Agro-bioresources, South China Agricultural University, Guangzhou, Guangdong, China
- The Key Laboratory of Plant Molecular Breeding of Guangdong Province, College of Agriculture, South China Agricultural University, Guangzhou, Guangdong, China
- Guangdong Laboratory for Lingnan Modern Agriculture, Guangzhou, Guangdong, China
| | - Jia Jia
- The State Key Laboratory for Conservation and Utilization of Subtropical Agro-bioresources, South China Agricultural University, Guangzhou, Guangdong, China
- The Key Laboratory of Plant Molecular Breeding of Guangdong Province, College of Agriculture, South China Agricultural University, Guangzhou, Guangdong, China
- Guangdong Laboratory for Lingnan Modern Agriculture, Guangzhou, Guangdong, China
| | - Riqian Liu
- The State Key Laboratory for Conservation and Utilization of Subtropical Agro-bioresources, South China Agricultural University, Guangzhou, Guangdong, China
- The Key Laboratory of Plant Molecular Breeding of Guangdong Province, College of Agriculture, South China Agricultural University, Guangzhou, Guangdong, China
- Guangdong Laboratory for Lingnan Modern Agriculture, Guangzhou, Guangdong, China
| | - Ruqian Wei
- The State Key Laboratory for Conservation and Utilization of Subtropical Agro-bioresources, South China Agricultural University, Guangzhou, Guangdong, China
- The Key Laboratory of Plant Molecular Breeding of Guangdong Province, College of Agriculture, South China Agricultural University, Guangzhou, Guangdong, China
- Guangdong Laboratory for Lingnan Modern Agriculture, Guangzhou, Guangdong, China
| | - Zhibin Guo
- The State Key Laboratory for Conservation and Utilization of Subtropical Agro-bioresources, South China Agricultural University, Guangzhou, Guangdong, China
- The Key Laboratory of Plant Molecular Breeding of Guangdong Province, College of Agriculture, South China Agricultural University, Guangzhou, Guangdong, China
- Guangdong Laboratory for Lingnan Modern Agriculture, Guangzhou, Guangdong, China
| | - Zhandong Cai
- The State Key Laboratory for Conservation and Utilization of Subtropical Agro-bioresources, South China Agricultural University, Guangzhou, Guangdong, China
- The Key Laboratory of Plant Molecular Breeding of Guangdong Province, College of Agriculture, South China Agricultural University, Guangzhou, Guangdong, China
- Guangdong Laboratory for Lingnan Modern Agriculture, Guangzhou, Guangdong, China
| | - Bo Chen
- The State Key Laboratory for Conservation and Utilization of Subtropical Agro-bioresources, South China Agricultural University, Guangzhou, Guangdong, China
- The Key Laboratory of Plant Molecular Breeding of Guangdong Province, College of Agriculture, South China Agricultural University, Guangzhou, Guangdong, China
- Guangdong Laboratory for Lingnan Modern Agriculture, Guangzhou, Guangdong, China
| | - Fuwei Liang
- The State Key Laboratory for Conservation and Utilization of Subtropical Agro-bioresources, South China Agricultural University, Guangzhou, Guangdong, China
- The Key Laboratory of Plant Molecular Breeding of Guangdong Province, College of Agriculture, South China Agricultural University, Guangzhou, Guangdong, China
- Guangdong Laboratory for Lingnan Modern Agriculture, Guangzhou, Guangdong, China
| | - Qiuju Xia
- Rice Molecular Breeding Institute, Granlux Associated Grains, Shenzhen, Guangdong, China
| | - Hai Nian
- The State Key Laboratory for Conservation and Utilization of Subtropical Agro-bioresources, South China Agricultural University, Guangzhou, Guangdong, China
- The Key Laboratory of Plant Molecular Breeding of Guangdong Province, College of Agriculture, South China Agricultural University, Guangzhou, Guangdong, China
- Guangdong Laboratory for Lingnan Modern Agriculture, Guangzhou, Guangdong, China
| | - Yanbo Cheng
- The State Key Laboratory for Conservation and Utilization of Subtropical Agro-bioresources, South China Agricultural University, Guangzhou, Guangdong, China
- The Key Laboratory of Plant Molecular Breeding of Guangdong Province, College of Agriculture, South China Agricultural University, Guangzhou, Guangdong, China
- Guangdong Laboratory for Lingnan Modern Agriculture, Guangzhou, Guangdong, China
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Zhong Y, Wen K, Li X, Wang S, Li S, Zeng Y, Cheng Y, Ma Q, Nian H. Identification and Mapping of QTLs for Sulfur-Containing Amino Acids in Soybean ( Glycine max L.). JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY 2023; 71:398-410. [PMID: 36574335 DOI: 10.1021/acs.jafc.2c05896] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/17/2023]
Abstract
Soybean is a major source of high-quality protein for humans and animals. The content of sulfur-containing amino acids (SAA) in soybean is insufficient, which has become the main factor limiting soybean nutrition. In this study, we used the high-density genetic maps derived from Guizao 1 and Brazil 13 to evaluate the quantitative trait loci of cysteine (Cys), methionine (Met), SAA, glycinin (7S), β-conglycinin (11S), ratio of glycinin to β-conglycinin (RGC), and protein content (PC). In genetic map linkage analysis, the major and stable 44 QTLs were detected, which shared nine bin intervals. Among them, the bin interval (bin157-bin160) on chromosome 5 was detected in multiple environments as a stable QTL, which was linked to 11S, 7S, RGC, and SSA. Based on the analysis of bioinformatics and RNA-sequencing data, 16 differentially expressed genes (DEGs) within these QTLs were selected as candidate genes. These results will help to elucidate the genetic mechanism of soybean SAA-related traits and provide the basis for the gene mining of sulfur-containing amino acids.
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Affiliation(s)
- Yiwang Zhong
- The State Key Laboratory for Conservation and Utilization of Subtropical Agro-bioresources, South China Agricultural University, Guangzhou 510642, Guangdong, People's Republic of China
- Guangdong Laboratory for Lingnan Modern Agriculture, Guangzhou 510642, Guangdong, People's Republic of China
- The Guangdong Subcenter of the National Center for Soybean Improvement, College of Agriculture, South China Agricultural University, Guangzhou 510642, Guangdong, People's Republic of China
| | - Ke Wen
- The State Key Laboratory for Conservation and Utilization of Subtropical Agro-bioresources, South China Agricultural University, Guangzhou 510642, Guangdong, People's Republic of China
- Guangdong Laboratory for Lingnan Modern Agriculture, Guangzhou 510642, Guangdong, People's Republic of China
- The Guangdong Subcenter of the National Center for Soybean Improvement, College of Agriculture, South China Agricultural University, Guangzhou 510642, Guangdong, People's Republic of China
- Key Laboratory of Vegetable Biology of Hainan Province, Vegetable Research Institute of Hainan Academy of Agricultural Sciences, Haikou 570228, Hainan, People's Republic of China
- Hainan Yazhou Bay Seed Laboratory, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Sanya 572025, Hainan, People's Republic of China
| | - Xingang Li
- The State Key Laboratory for Conservation and Utilization of Subtropical Agro-bioresources, South China Agricultural University, Guangzhou 510642, Guangdong, People's Republic of China
- Guangdong Laboratory for Lingnan Modern Agriculture, Guangzhou 510642, Guangdong, People's Republic of China
- The Guangdong Subcenter of the National Center for Soybean Improvement, College of Agriculture, South China Agricultural University, Guangzhou 510642, Guangdong, People's Republic of China
| | - Shasha Wang
- The State Key Laboratory for Conservation and Utilization of Subtropical Agro-bioresources, South China Agricultural University, Guangzhou 510642, Guangdong, People's Republic of China
- Guangdong Laboratory for Lingnan Modern Agriculture, Guangzhou 510642, Guangdong, People's Republic of China
- The Guangdong Subcenter of the National Center for Soybean Improvement, College of Agriculture, South China Agricultural University, Guangzhou 510642, Guangdong, People's Republic of China
| | - Sansan Li
- The State Key Laboratory for Conservation and Utilization of Subtropical Agro-bioresources, South China Agricultural University, Guangzhou 510642, Guangdong, People's Republic of China
- Guangdong Laboratory for Lingnan Modern Agriculture, Guangzhou 510642, Guangdong, People's Republic of China
- The Guangdong Subcenter of the National Center for Soybean Improvement, College of Agriculture, South China Agricultural University, Guangzhou 510642, Guangdong, People's Republic of China
| | - Yuhong Zeng
- The State Key Laboratory for Conservation and Utilization of Subtropical Agro-bioresources, South China Agricultural University, Guangzhou 510642, Guangdong, People's Republic of China
- Guangdong Laboratory for Lingnan Modern Agriculture, Guangzhou 510642, Guangdong, People's Republic of China
- The Guangdong Subcenter of the National Center for Soybean Improvement, College of Agriculture, South China Agricultural University, Guangzhou 510642, Guangdong, People's Republic of China
| | - Yanbo Cheng
- The State Key Laboratory for Conservation and Utilization of Subtropical Agro-bioresources, South China Agricultural University, Guangzhou 510642, Guangdong, People's Republic of China
- Guangdong Laboratory for Lingnan Modern Agriculture, Guangzhou 510642, Guangdong, People's Republic of China
- The Guangdong Subcenter of the National Center for Soybean Improvement, College of Agriculture, South China Agricultural University, Guangzhou 510642, Guangdong, People's Republic of China
| | - Qibin Ma
- The State Key Laboratory for Conservation and Utilization of Subtropical Agro-bioresources, South China Agricultural University, Guangzhou 510642, Guangdong, People's Republic of China
- Guangdong Laboratory for Lingnan Modern Agriculture, Guangzhou 510642, Guangdong, People's Republic of China
- The Guangdong Subcenter of the National Center for Soybean Improvement, College of Agriculture, South China Agricultural University, Guangzhou 510642, Guangdong, People's Republic of China
| | - Hai Nian
- The State Key Laboratory for Conservation and Utilization of Subtropical Agro-bioresources, South China Agricultural University, Guangzhou 510642, Guangdong, People's Republic of China
- Guangdong Laboratory for Lingnan Modern Agriculture, Guangzhou 510642, Guangdong, People's Republic of China
- The Guangdong Subcenter of the National Center for Soybean Improvement, College of Agriculture, South China Agricultural University, Guangzhou 510642, Guangdong, People's Republic of China
- Hainan Yazhou Bay Seed Laboratory, Sanya Nanfan Research Institute of Hainan University, Sanya 572025, Hainan, People's Republic of China
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20
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Rebollo-Hernanz M, Bringe NA, Gonzalez de Mejia E. Selected Soybean Varieties Regulate Hepatic LDL-Cholesterol Homeostasis Depending on Their Glycinin:β-Conglycinin Ratio. Antioxidants (Basel) 2022; 12:antiox12010020. [PMID: 36670883 PMCID: PMC9855081 DOI: 10.3390/antiox12010020] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2022] [Revised: 12/15/2022] [Accepted: 12/17/2022] [Indexed: 12/24/2022] Open
Abstract
Clinical studies indicate that the consumption of soybean protein might reduce cholesterol and LDL levels preventing the development of atherosclerotic cardiovascular diseases. However, soybean variety can influence soybean protein profile and therefore affect soybean protein health-promoting properties. This study investigated the composition and effects of nineteen soybean varieties digested under simulated gastrointestinal conditions on hepatic cholesterol metabolism and LDL oxidation in vitro. Soybean varieties exhibited a differential protein hydrolysis during gastrointestinal digestion. Soybean varieties could be classified according to their composition (high/low glycinin:β-conglycinin ratio) and capacity to inhibit HMGCR (IC50 from 59 to 229 µg protein mL−1). According to multivariate analyses, five soybean varieties were selected. These soybean varieties produced different peptide profiles and differently reduced cholesterol concentration (43−55%) by inhibiting HMGCR in fatty-acid-stimulated HepG2 hepatocytes. Selected digested soybean varieties inhibited cholesterol esterification, triglyceride production, VLDL secretion, and LDL recycling by reducing ANGPTL3 and PCSK9 and synchronously increasing LDLR expression. In addition, selected soybean varieties hindered LDL oxidation, reducing the formation of lipid peroxidation early (conjugated dienes) and end products (malondialdehyde and 4-hydroxynonenal). The changes in HMGCR expression, cholesterol esterification, triglyceride accumulation, ANGPTL3 release, and malondialdehyde formation during LDL oxidation were significantly (p < 0.05) correlated with the glycinin:β-conglycinin ratio. Soybean varieties with lower glycinin:β-conglycinin exhibited a better potential in regulating cholesterol and LDL homeostasis in vitro. Consumption of soybean flour with a greater proportion of β-conglycinin may, consequently, improve the potential of the food ingredient to maintain healthy liver cholesterol homeostasis and cardiovascular function.
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Affiliation(s)
- Miguel Rebollo-Hernanz
- Department of Food Science and Human Nutrition, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
| | | | - Elvira Gonzalez de Mejia
- Department of Food Science and Human Nutrition, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
- Correspondence: ; Tel.: +1-217-244-3196
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21
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Hudson K. Soybean Protein and Oil Variants Identified through a Forward Genetic Screen for Seed Composition. PLANTS (BASEL, SWITZERLAND) 2022; 11:2966. [PMID: 36365419 PMCID: PMC9656176 DOI: 10.3390/plants11212966] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/30/2022] [Revised: 10/25/2022] [Accepted: 10/31/2022] [Indexed: 06/16/2023]
Abstract
Mutagenesis remains an important tool in soybean biology. In classical plant mutation breeding, mutagenesis has been a trusted approach for decades, creating stable non-transgenic variation, and many mutations have been incorporated into germplasm for several crops, especially to introduce favorable seed composition traits. We performed a genetic screen for aberrant oil or protein composition of soybean seeds, and as a result isolated over 100 mutant lines for seed composition phenotypes, with particular interest in high protein or high oil phenotypes. These lines were followed for multiple seasons and generations to select the most stable traits for further characterization. Through backcrossing and outcrossing experiments, we determined that a subset of the lines showed recessive inheritance, while others showed a dominant inheritance pattern that suggests the involvement of multiple loci and genetic mechanisms. These lines can be used as a resource for future studies of the genetic control of seed protein and oil content in soybean.
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Affiliation(s)
- Karen Hudson
- USDA-ARS Crop Production and Pest Control Research Unit, 915 West State Street, West Lafayette, IN 47907, USA
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22
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Peptide release, radical scavenging capacity, and antioxidant responses in intestinal cells are determined by soybean variety and gastrointestinal digestion under simulated conditions. Food Chem 2022. [DOI: 10.1016/j.foodchem.2022.134929] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
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23
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Guo B, Sun L, Jiang S, Ren H, Sun R, Wei Z, Hong H, Luan X, Wang J, Wang X, Xu D, Li W, Guo C, Qiu LJ. Soybean genetic resources contributing to sustainable protein production. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2022; 135:4095-4121. [PMID: 36239765 PMCID: PMC9561314 DOI: 10.1007/s00122-022-04222-9] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/22/2022] [Accepted: 09/10/2022] [Indexed: 06/12/2023]
Abstract
KEY MESSAGE Genetic resources contributes to the sustainable protein production in soybean. Soybean is an important crop for food, oil, and forage and is the main source of edible vegetable oil and vegetable protein. It plays an important role in maintaining balanced dietary nutrients for human health. The soybean protein content is a quantitative trait mainly controlled by gene additive effects and is usually negatively correlated with agronomic traits such as the oil content and yield. The selection of soybean varieties with high protein content and high yield to secure sustainable protein production is one of the difficulties in soybean breeding. The abundant genetic variation of soybean germplasm resources is the basis for overcoming the obstacles in breeding for soybean varieties with high yield and high protein content. Soybean has been cultivated for more than 5000 years and has spread from China to other parts of the world. The rich genetic resources play an important role in promoting the sustainable production of soybean protein worldwide. In this paper, the origin and spread of soybean and the current status of soybean production are reviewed; the genetic characteristics of soybean protein and the distribution of resources are expounded based on phenotypes; the discovery of soybean seed protein-related genes as well as transcriptomic, metabolomic, and proteomic studies in soybean are elaborated; the creation and utilization of high-protein germplasm resources are introduced; and the prospect of high-protein soybean breeding is described.
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Affiliation(s)
- Bingfu Guo
- Nanchang Branch of National Center of Oil crops Improvement, Jiangxi Province Key Laboratory of Oil crops Biology, Crops Research Institute of Jiangxi Academy of Agricultural Sciences, Nanchang, China
- The National Key Facility for Crop Gene Resources and Genetic Improvement (NFCRI) and MOA KeyLab of Soybean Biology (Beijing), Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Liping Sun
- Nanchang Branch of National Center of Oil crops Improvement, Jiangxi Province Key Laboratory of Oil crops Biology, Crops Research Institute of Jiangxi Academy of Agricultural Sciences, Nanchang, China
| | - Siqi Jiang
- Key Laboratory of Molecular Cytogenetics and Genetic Breeding, College of Life Science and Technology, Harbin Normal University, Harbin, China
- The National Key Facility for Crop Gene Resources and Genetic Improvement (NFCRI) and MOA KeyLab of Soybean Biology (Beijing), Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Honglei Ren
- Soybean Research Institute, Heilongjiang Academy of Agricultural Sciences, Harbin, China
| | - Rujian Sun
- The National Key Facility for Crop Gene Resources and Genetic Improvement (NFCRI) and MOA KeyLab of Soybean Biology (Beijing), Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Zhongyan Wei
- The National Key Facility for Crop Gene Resources and Genetic Improvement (NFCRI) and MOA KeyLab of Soybean Biology (Beijing), Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Huilong Hong
- The National Key Facility for Crop Gene Resources and Genetic Improvement (NFCRI) and MOA KeyLab of Soybean Biology (Beijing), Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing, China
- Soybean Research Institute, Key Laboratory of Soybean Biology of Chinese Education Ministry, Northeast Agriculture University, Harbin, China
| | - Xiaoyan Luan
- Soybean Research Institute, Heilongjiang Academy of Agricultural Sciences, Harbin, China
| | - Jun Wang
- College of Agriculture, Yangtze University, Jingzhou, China
| | - Xiaobo Wang
- School of Agronomy, Anhui Agricultural University, Hefei, China
| | - Donghe Xu
- Biological Resources and Post-Harvest Division, Japan International Research Center for Agricultural Sciences, Tsukuba, Japan
| | - Wenbin Li
- Soybean Research Institute, Key Laboratory of Soybean Biology of Chinese Education Ministry, Northeast Agriculture University, Harbin, China
| | - Changhong Guo
- Key Laboratory of Molecular Cytogenetics and Genetic Breeding, College of Life Science and Technology, Harbin Normal University, Harbin, China
| | - Li-Juan Qiu
- The National Key Facility for Crop Gene Resources and Genetic Improvement (NFCRI) and MOA KeyLab of Soybean Biology (Beijing), Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing, China.
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24
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Duan Z, Zhang M, Zhang Z, Liang S, Fan L, Yang X, Yuan Y, Pan Y, Zhou G, Liu S, Tian Z. Natural allelic variation of GmST05 controlling seed size and quality in soybean. PLANT BIOTECHNOLOGY JOURNAL 2022; 20:1807-1818. [PMID: 35642379 PMCID: PMC9398382 DOI: 10.1111/pbi.13865] [Citation(s) in RCA: 40] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/06/2022] [Revised: 05/23/2022] [Accepted: 05/27/2022] [Indexed: 05/26/2023]
Abstract
Seed size is one of the most important agronomic traits determining the yield of crops. Cloning the key genes controlling seed size and pyramiding their elite alleles will facilitate yield improvement. To date, few genes controlling seed size have been identified in soybean, a major crop that provides half of the plant oil and one quarter of the plant protein globally. Here, through a genome-wide association study of over 1800 soybean accessions, we determined that natural allelic variation at GmST05 (Seed Thickness 05) predominantly controlled seed thickness and size in soybean germplasm. Further analyses suggested that the two major haplotypes of GmST05 differed significantly at the transcriptional level. Transgenic experiments demonstrated that GmST05 positively regulated seed size and influenced oil and protein contents, possibly by regulating the transcription of GmSWEET10a. Population genetic diversity analysis suggested that allelic variations of GmST05 were selected during geographical differentiation but have not been fixed. In summary, natural variation in GmST05 determines transcription levels and influences seed size and quality in soybean, making it an important gene resource for soybean molecular breeding.
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Affiliation(s)
- Zongbiao Duan
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental BiologyChinese Academy of SciencesBeijingChina
- University of Chinese Academy of SciencesBeijingChina
| | - Min Zhang
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental BiologyChinese Academy of SciencesBeijingChina
| | - Zhifang Zhang
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental BiologyChinese Academy of SciencesBeijingChina
| | - Shan Liang
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental BiologyChinese Academy of SciencesBeijingChina
- University of Chinese Academy of SciencesBeijingChina
| | - Lei Fan
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental BiologyChinese Academy of SciencesBeijingChina
| | - Xia Yang
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental BiologyChinese Academy of SciencesBeijingChina
- University of Chinese Academy of SciencesBeijingChina
| | - Yaqin Yuan
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental BiologyChinese Academy of SciencesBeijingChina
- University of Chinese Academy of SciencesBeijingChina
| | - Yi Pan
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental BiologyChinese Academy of SciencesBeijingChina
| | - Guoan Zhou
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental BiologyChinese Academy of SciencesBeijingChina
| | - Shulin Liu
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental BiologyChinese Academy of SciencesBeijingChina
| | - Zhixi Tian
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental BiologyChinese Academy of SciencesBeijingChina
- University of Chinese Academy of SciencesBeijingChina
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25
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Yang Y, La TC, Gillman JD, Lyu Z, Joshi T, Usovsky M, Song Q, Scaboo A. Linkage analysis and residual heterozygotes derived near isogenic lines reveals a novel protein quantitative trait loci from a Glycine soja accession. FRONTIERS IN PLANT SCIENCE 2022; 13:938100. [PMID: 35968122 PMCID: PMC9372550 DOI: 10.3389/fpls.2022.938100] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/06/2022] [Accepted: 07/07/2022] [Indexed: 06/15/2023]
Abstract
Modern soybean [Glycine max (L.) Merr] cultivars have low overall genetic variation due to repeated bottleneck events that arose during domestication and from selection strategies typical of many soybean breeding programs. In both public and private soybean breeding programs, the introgression of wild soybean (Glycine soja Siebold and Zucc.) alleles is a viable option to increase genetic diversity and identify new sources for traits of value. The objectives of our study were to examine the genetic architecture responsible for seed protein and oil using a recombinant inbred line (RIL) population derived from hybridizing a G. max line ('Osage') with a G. soja accession (PI 593983). Linkage mapping identified a total of seven significant quantitative trait loci on chromosomes 14 and 20 for seed protein and on chromosome 8 for seed oil with LOD scores ranging from 5.3 to 31.7 for seed protein content and from 9.8 to 25.9 for seed oil content. We analyzed 3,015 single F4:9 soybean plants to develop two residual heterozygotes derived near isogenic lines (RHD-NIL) populations by targeting nine SNP markers from genotype-by-sequencing, which corresponded to two novel quantitative trait loci (QTL) derived from G. soja: one for a novel seed oil QTL on chromosome 8 and another for a novel protein QTL on chromosome 14. Single marker analysis and linkage analysis using 50 RHD-NILs validated the chromosome 14 protein QTL, and whole genome sequencing of RHD-NILs allowed us to reduce the QTL interval from ∼16.5 to ∼4.6 Mbp. We identified two genomic regions based on recombination events which had significant increases of 0.65 and 0.72% in seed protein content without a significant decrease in seed oil content. A new Kompetitive allele-specific polymerase chain reaction (KASP) assay, which will be useful for introgression of this trait into modern elite G. max cultivars, was developed in one region. Within the significantly associated genomic regions, a total of eight genes are considered as candidate genes, based on the presence of gene annotations associated with the protein or amino acid metabolism/movement. Our results provide better insights into utilizing wild soybean as a source of genetic diversity for soybean cultivar improvement utilizing native traits.
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Affiliation(s)
- Yia Yang
- Division of Plant Science and Technology, University of Missouri, Columbia, MO, United States
| | - Thang C. La
- Division of Plant Science and Technology, University of Missouri, Columbia, MO, United States
| | - Jason D. Gillman
- Plant Genetics Research Unit, United States Department of Agriculture-Agricultural Research Service, Columbia, MO, United States
| | - Zhen Lyu
- Department of Electrical Engineering and Computer Science, University of Missouri, Columbia, MO, United States
| | - Trupti Joshi
- Department of Health Management and Informatics, MU Institute of Data Science and Informatics and Christopher S. Bond Life Science Center, University of Missouri, Columbia, MO, United States
| | - Mariola Usovsky
- Division of Plant Science and Technology, University of Missouri, Columbia, MO, United States
| | - Qijian Song
- Soybean Genomics and Improvement Laboratory, United States Department of Agriculture-Agricultural Research Service, Beltsville, MD, United States
| | - Andrew Scaboo
- Division of Plant Science and Technology, University of Missouri, Columbia, MO, United States
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26
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Feng W, Fu L, Fu M, Sang Z, Wang Y, Wang L, Ren H, Du W, Hao X, Sun L, Zhang J, Wang W, Xing G, He J, Gai J. Transgressive Potential Prediction and Optimal Cross Design of Seed Protein Content in the Northeast China Soybean Population Based on Full Exploration of the QTL-Allele System. FRONTIERS IN PLANT SCIENCE 2022; 13:896549. [PMID: 35903228 PMCID: PMC9317943 DOI: 10.3389/fpls.2022.896549] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/15/2022] [Accepted: 06/09/2022] [Indexed: 06/12/2023]
Abstract
Northeast China is a major soybean production region in China. A representative sample of the Northeast China soybean germplasm population (NECSGP) composed of 361 accessions was evaluated for their seed protein content (SPC) in Tieling, Northeast China. This SPC varied greatly, with a mean SPC of 40.77%, ranging from 36.60 to 46.07%, but it was lower than that of the Chinese soybean landrace population (43.10%, ranging from 37.51 to 50.46%). The SPC increased slightly from 40.32-40.97% in the old maturity groups (MG, MGIII + II + I) to 40.93-41.58% in the new MGs (MG0 + 00 + 000). The restricted two-stage multi-locus genome-wide association study (RTM-GWAS) with 15,501 SNP linkage-disequilibrium block (SNPLDB) markers identified 73 SPC quantitative trait loci (QTLs) with 273 alleles, explaining 71.70% of the phenotypic variation, wherein 28 QTLs were new ones. The evolutionary changes of QTL-allele structures from old MGs to new MGs were analyzed, and 97.79% of the alleles in new MGs were inherited from the old MGs and 2.21% were new. The small amount of new positive allele emergence and possible recombination between alleles might explain the slight SPC increase in the new MGs. The prediction of recombination potentials in the SPC of all the possible crosses indicated that the mean of SPC overall crosses was 43.29% (+2.52%) and the maximum was 50.00% (+9.23%) in the SPC, and the maximum transgressive potential was 3.93%, suggesting that SPC breeding potentials do exist in the NECSGP. A total of 120 candidate genes were annotated and functionally classified into 13 categories, indicating that SPC is a complex trait conferred by a gene network.
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Affiliation(s)
- Weidan Feng
- Soybean Research Institute/MARA National Center for Soybean Improvement/MARA Key Laboratory of Biology and Genetic Improvement of Soybean (General), Nanjing Agricultural University, Nanjing, China
- State Key Laboratory for Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, China
| | - Lianshun Fu
- Tieling Academy of Agricultural Sciences, Tieling, China
| | - Mengmeng Fu
- Soybean Research Institute/MARA National Center for Soybean Improvement/MARA Key Laboratory of Biology and Genetic Improvement of Soybean (General), Nanjing Agricultural University, Nanjing, China
| | - Ziqian Sang
- Soybean Research Institute/MARA National Center for Soybean Improvement/MARA Key Laboratory of Biology and Genetic Improvement of Soybean (General), Nanjing Agricultural University, Nanjing, China
| | - Yanping Wang
- Mudanjiang Research and Development Center for Soybean/Mudanjiang Experiment Station of the National Center for Soybean Improvement, Mudanjiang Branch of Heilongjiang Academy of Agricultural Sciences, Mudanjiang, China
| | - Lei Wang
- Soybean Research Institute/MARA National Center for Soybean Improvement/MARA Key Laboratory of Biology and Genetic Improvement of Soybean (General), Nanjing Agricultural University, Nanjing, China
- State Key Laboratory for Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, China
| | - Haixiang Ren
- Mudanjiang Research and Development Center for Soybean/Mudanjiang Experiment Station of the National Center for Soybean Improvement, Mudanjiang Branch of Heilongjiang Academy of Agricultural Sciences, Mudanjiang, China
| | - Weiguang Du
- Mudanjiang Research and Development Center for Soybean/Mudanjiang Experiment Station of the National Center for Soybean Improvement, Mudanjiang Branch of Heilongjiang Academy of Agricultural Sciences, Mudanjiang, China
| | - Xiaoshuai Hao
- Soybean Research Institute/MARA National Center for Soybean Improvement/MARA Key Laboratory of Biology and Genetic Improvement of Soybean (General), Nanjing Agricultural University, Nanjing, China
- State Key Laboratory for Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, China
| | - Lei Sun
- Soybean Research Institute/MARA National Center for Soybean Improvement/MARA Key Laboratory of Biology and Genetic Improvement of Soybean (General), Nanjing Agricultural University, Nanjing, China
- State Key Laboratory for Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, China
| | - Jiaoping Zhang
- Soybean Research Institute/MARA National Center for Soybean Improvement/MARA Key Laboratory of Biology and Genetic Improvement of Soybean (General), Nanjing Agricultural University, Nanjing, China
- State Key Laboratory for Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, China
| | - Wubin Wang
- Soybean Research Institute/MARA National Center for Soybean Improvement/MARA Key Laboratory of Biology and Genetic Improvement of Soybean (General), Nanjing Agricultural University, Nanjing, China
- State Key Laboratory for Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, China
| | - Guangnan Xing
- Soybean Research Institute/MARA National Center for Soybean Improvement/MARA Key Laboratory of Biology and Genetic Improvement of Soybean (General), Nanjing Agricultural University, Nanjing, China
- State Key Laboratory for Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, China
| | - Jianbo He
- Soybean Research Institute/MARA National Center for Soybean Improvement/MARA Key Laboratory of Biology and Genetic Improvement of Soybean (General), Nanjing Agricultural University, Nanjing, China
- State Key Laboratory for Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, China
| | - Junyi Gai
- Soybean Research Institute/MARA National Center for Soybean Improvement/MARA Key Laboratory of Biology and Genetic Improvement of Soybean (General), Nanjing Agricultural University, Nanjing, China
- State Key Laboratory for Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, China
- Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing, China
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27
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Jha UC, Nayyar H, Parida SK, Deshmukh R, von Wettberg EJB, Siddique KHM. Ensuring Global Food Security by Improving Protein Content in Major Grain Legumes Using Breeding and 'Omics' Tools. Int J Mol Sci 2022; 23:7710. [PMID: 35887057 PMCID: PMC9325250 DOI: 10.3390/ijms23147710] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2022] [Revised: 07/05/2022] [Accepted: 07/05/2022] [Indexed: 11/16/2022] Open
Abstract
Grain legumes are a rich source of dietary protein for millions of people globally and thus a key driver for securing global food security. Legume plant-based 'dietary protein' biofortification is an economic strategy for alleviating the menace of rising malnutrition-related problems and hidden hunger. Malnutrition from protein deficiency is predominant in human populations with an insufficient daily intake of animal protein/dietary protein due to economic limitations, especially in developing countries. Therefore, enhancing grain legume protein content will help eradicate protein-related malnutrition problems in low-income and underprivileged countries. Here, we review the exploitable genetic variability for grain protein content in various major grain legumes for improving the protein content of high-yielding, low-protein genotypes. We highlight classical genetics-based inheritance of protein content in various legumes and discuss advances in molecular marker technology that have enabled us to underpin various quantitative trait loci controlling seed protein content (SPC) in biparental-based mapping populations and genome-wide association studies. We also review the progress of functional genomics in deciphering the underlying candidate gene(s) controlling SPC in various grain legumes and the role of proteomics and metabolomics in shedding light on the accumulation of various novel proteins and metabolites in high-protein legume genotypes. Lastly, we detail the scope of genomic selection, high-throughput phenotyping, emerging genome editing tools, and speed breeding protocols for enhancing SPC in grain legumes to achieve legume-based dietary protein security and thus reduce the global hunger risk.
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Affiliation(s)
- Uday C. Jha
- ICAR—Indian Institute of Pulses Research (IIPR), Kanpur 208024, India
| | - Harsh Nayyar
- Department of Botany, Panjab University, Chandigarh 160014, India;
| | - Swarup K. Parida
- National Institute of Plant Genome Research, New Delhi 110067, India;
| | - Rupesh Deshmukh
- National Agri-Food Biotechnology Institute, Punjab 140308, India;
| | | | - Kadambot H. M. Siddique
- The UWA Institute of Agriculture, The University of Western Australia, Perth, WA 6001, Australia
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Qin J, Wang F, Zhao Q, Shi A, Zhao T, Song Q, Ravelombola W, An H, Yan L, Yang C, Zhang M. Identification of Candidate Genes and Genomic Selection for Seed Protein in Soybean Breeding Pipeline. FRONTIERS IN PLANT SCIENCE 2022; 13:882732. [PMID: 35783963 PMCID: PMC9244705 DOI: 10.3389/fpls.2022.882732] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/24/2022] [Accepted: 05/16/2022] [Indexed: 05/13/2023]
Abstract
Soybean is a primary meal protein for human consumption, poultry, and livestock feed. In this study, quantitative trait locus (QTL) controlling protein content was explored via genome-wide association studies (GWAS) and linkage mapping approaches based on 284 soybean accessions and 180 recombinant inbred lines (RILs), respectively, which were evaluated for protein content for 4 years. A total of 22 single nucleotide polymorphisms (SNPs) associated with protein content were detected using mixed linear model (MLM) and general linear model (GLM) methods in Tassel and 5 QTLs using Bayesian interval mapping (IM), single-trait multiple interval mapping (SMIM), single-trait composite interval mapping maximum likelihood estimation (SMLE), and single marker regression (SMR) models in Q-Gene and IciMapping. Major QTLs were detected on chromosomes 6 and 20 in both populations. The new QTL genomic region on chromosome 6 (Chr6_18844283-19315351) included 7 candidate genes and the Hap.X AA at the Chr6_19172961 position was associated with high protein content. Genomic selection (GS) of protein content was performed using Bayesian Lasso (BL) and ridge regression best linear unbiased prediction (rrBULP) based on all the SNPs and the SNPs significantly associated with protein content resulted from GWAS. The results showed that BL and rrBLUP performed similarly; GS accuracy was dependent on the SNP set and training population size. GS efficiency was higher for the SNPs derived from GWAS than random SNPs and reached a plateau when the number of markers was >2,000. The SNP markers identified in this study and other information were essential in establishing an efficient marker-assisted selection (MAS) and GS pipelines for improving soybean protein content.
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Affiliation(s)
- Jun Qin
- National Soybean Improvement Center Shijiazhuang Sub-Center, North China Key Laboratory of Biology and Genetic Improvement of Soybean, Ministry of Agriculture, Hebei Laboratory of Crop Genetics and Breeding, Cereal & Oil Crop Institute, Hebei Academy of Agricultural and Forestry Sciences, Shijiazhuang, China
| | - Fengmin Wang
- National Soybean Improvement Center Shijiazhuang Sub-Center, North China Key Laboratory of Biology and Genetic Improvement of Soybean, Ministry of Agriculture, Hebei Laboratory of Crop Genetics and Breeding, Cereal & Oil Crop Institute, Hebei Academy of Agricultural and Forestry Sciences, Shijiazhuang, China
| | - Qingsong Zhao
- National Soybean Improvement Center Shijiazhuang Sub-Center, North China Key Laboratory of Biology and Genetic Improvement of Soybean, Ministry of Agriculture, Hebei Laboratory of Crop Genetics and Breeding, Cereal & Oil Crop Institute, Hebei Academy of Agricultural and Forestry Sciences, Shijiazhuang, China
| | - Ainong Shi
- Department of Horticulture, University of Arkansas, Fayetteville, AR, United States
- *Correspondence: Ainong Shi,
| | - Tiantian Zhao
- National Soybean Improvement Center Shijiazhuang Sub-Center, North China Key Laboratory of Biology and Genetic Improvement of Soybean, Ministry of Agriculture, Hebei Laboratory of Crop Genetics and Breeding, Cereal & Oil Crop Institute, Hebei Academy of Agricultural and Forestry Sciences, Shijiazhuang, China
| | - Qijian Song
- Soybean Genomics and Improvement Lab, United States Department of Agriculture - Agricultural Research Service (USDA-ARS), Beltsville, MD, United States
| | - Waltram Ravelombola
- Department of Soil and Crop Sciences, Texas A&M University, College Station, TX, United States
| | - Hongzhou An
- National Soybean Improvement Center Shijiazhuang Sub-Center, North China Key Laboratory of Biology and Genetic Improvement of Soybean, Ministry of Agriculture, Hebei Laboratory of Crop Genetics and Breeding, Cereal & Oil Crop Institute, Hebei Academy of Agricultural and Forestry Sciences, Shijiazhuang, China
| | - Long Yan
- National Soybean Improvement Center Shijiazhuang Sub-Center, North China Key Laboratory of Biology and Genetic Improvement of Soybean, Ministry of Agriculture, Hebei Laboratory of Crop Genetics and Breeding, Cereal & Oil Crop Institute, Hebei Academy of Agricultural and Forestry Sciences, Shijiazhuang, China
| | - Chunyan Yang
- National Soybean Improvement Center Shijiazhuang Sub-Center, North China Key Laboratory of Biology and Genetic Improvement of Soybean, Ministry of Agriculture, Hebei Laboratory of Crop Genetics and Breeding, Cereal & Oil Crop Institute, Hebei Academy of Agricultural and Forestry Sciences, Shijiazhuang, China
- Chunyan Yang,
| | - Mengchen Zhang
- National Soybean Improvement Center Shijiazhuang Sub-Center, North China Key Laboratory of Biology and Genetic Improvement of Soybean, Ministry of Agriculture, Hebei Laboratory of Crop Genetics and Breeding, Cereal & Oil Crop Institute, Hebei Academy of Agricultural and Forestry Sciences, Shijiazhuang, China
- Mengchen Zhang,
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Zuo JF, Ikram M, Liu JY, Han CY, Niu Y, Dunwell JM, Zhang YM. Domestication and improvement genes reveal the differences of seed size- and oil-related traits in soybean domestication and improvement. Comput Struct Biotechnol J 2022; 20:2951-2964. [PMID: 35782726 PMCID: PMC9213226 DOI: 10.1016/j.csbj.2022.06.014] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2022] [Revised: 06/07/2022] [Accepted: 06/07/2022] [Indexed: 12/01/2022] Open
Abstract
Due to reduced diversity, it is essential to map domesticated and improved genes. 13 known and 442 candidate genes were mined for seed size- and oil-related traits. All the genes were used to explain trait changes in domestication and improvement. 56 domesticated and 15 improved genes may be valuable for future soybean breeding. This study provides useful gene resources for future breeding and biology research.
To address domestication and improvement studies of soybean seed size- and oil-related traits, a series of domesticated and improved regions, loci, and candidate genes were identified in 286 soybean accessions using domestication and improvement analyses, genome-wide association studies, quantitative trait locus (QTL) mapping and bulked segregant analyses in this study. As a result, 534 candidate domestication regions (CDRs) and 458 candidate improvement regions (CIRs) were identified in this study and integrated with those in five and three previous studies, respectively, to obtain 952 CDRs and 538 CIRs; 1469 loci for soybean seed size- and oil-related traits were identified in this study and integrated with those in Soybase to obtain 433 QTL clusters. The two results were intersected to obtain 245 domestication and 221 improvement loci for the above traits. Around these trait-related domestication and improvement loci, 7 domestication and 7 improvement genes were found to be truly associated with these traits, and 372 candidate domestication and 87 candidate improvement genes were identified using gene expression, SNP variants in genome, miRNA binding, KEGG pathway, DNA methylation, and haplotype analysis. These genes were used to explain the trait changes in domestication and improvement. As a result, the trait changes can be explained by their frequencies of elite haplotypes, base mutations in coding region, and three factors affecting their expression levels. In addition, 56 domestication and 15 improvement genes may be valuable for future soybean breeding. This study can provide useful gene resources for future soybean breeding and molecular biology research.
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Affiliation(s)
- Jian-Fang Zuo
- Crop Information Center, College of Plant Science and Technology, Huazhong Agricultural University, Wuhan, China
| | - Muhammad Ikram
- Crop Information Center, College of Plant Science and Technology, Huazhong Agricultural University, Wuhan, China
| | - Jin-Yang Liu
- Jiangsu Key Laboratory for Horticultural Crop Genetic Improvement, Institute of Industrial Crops, Jiangsu Academy of Agricultural Sciences, Nanjing, China
| | - Chun-Yu Han
- Crop Information Center, College of Plant Science and Technology, Huazhong Agricultural University, Wuhan, China
| | - Yuan Niu
- School of Life Sciences and Food Engineering, Huaiyin Institute of Technology, Huaian, China
| | - Jim M. Dunwell
- School of Agriculture, Policy and Development, University of Reading, Reading, United Kingdom
| | - Yuan-Ming Zhang
- Crop Information Center, College of Plant Science and Technology, Huazhong Agricultural University, Wuhan, China
- Corresponding author.
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